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Updated: Sep 16, 2025
Perturbations of Circulating miRNAs in Irritable Bowel Syndrome Detected Using a Multiplexed High-throughput Gene Expression Platform
Published on: November 30, 2016
Identification of potential transcriptomic and microRNA markers to assess benralizumab effectiveness
Keita Hirai1, Toshihiro Shirai2, Sekiko Uehara3
1Department of Clinical Pharmacology and Therapeutics, Shinshu University Graduate School of Medicine, Matsumoto, Japan; Department of Pharmacy, Shinshu University Hospital, Matsumoto, Japan; Department of Clinical Pharmacology and Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan.
Background:
Benralizumab targets IL-5 receptors and eliminates eosinophils, demonstrating its efficacy in type 2 inflammation-predominant asthma. Real-world evidence indicates variability in patient responses, emphasizing the need to understand the pathologic characteristics that influence its effectiveness.
Objective:
We postulated that patients with high and low benralizumab response would exhibit distinct pathophysiologic characteristics. We aimed to identify specific genes and microRNAs (miRNAs) as potential indicators of effectiveness-related characteristics.
Methods:
This prospective observational study included 17 patients with severe asthma undergoing benralizumab treatment. T-cell transcriptomic analysis was conducted before and 24 weeks after treatment initiation. To identify the genes associated with treatment efficacy, we identified differentially expressed genes (DEGs) and used a weighted gene coexpression network analysis. Additionally, serum miRNAs were analyzed quantitatively by using PCR arrays, and their correlation with gene clusters associated with treatment efficacy was investigated.
Results:
Transcriptomic analysis revealed that 223 DEGs were included in the response to benralizumab treatment. Weighted gene coexpression network analysis identified 21 coexpressed gene clusters, with most DEGs enriched in the 2 modules. One of these modules, the magenta module, was associated with the effectiveness of benralizumab treatment. Serum miRNA profiling identified 5 miRNAs associated with both treatment effectiveness and the magenta module (miR-7-5p, miR-155-5p, miR-320b, miR-342-3p, and miR-484). Among these, miR-7-5p showed the highest predictive accuracy for benralizumab effectiveness.
Conclusion:
This study recognized specific gene expression patterns and serum miRNAs associated with the effectiveness of benralizumab in treating severe asthma. These findings contribute to our understanding of the asthma endotypes and may improve patient selection for benralizumab treatment.
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